Community member post by Suzanne A. Pierce
Ask most 21st century citizens whether they like technology and they will respond with a resounding, “Yes!” Ask them why and you’ll get answers like, “Because it’s cool and technology is fun!” or “Technology systems help us learn and understand things.” Or “Technology helps us communicate with one another, keep up with current events, or share what we are doing.” Look at the day-to-day activities of most people on the planet and you’ll find that they use some form of technology to complete almost every activity that they undertake.
When you think about it, technologies are really just tools. And we humans are tool users of old. Evidence of tool use extends back to Neolithic times. Tools change our experience of the world around us and help us engage and interact more effectively. There are, of course, side effects from the rampant tool use of humans on a mass scale. For example, one need look no further than global transportation systems to see the social benefits and, simultaneously, massive impacts of human systems leveraging “tools” like cars, trains, cargo ships, planes, and so on, at scale.
Modern tool use has expanded to include a myriad of digital technologies and aids to everyday human activities. When it comes to complex systems, it’s no wonder then that we are reliant on technology and computational tools, like simulation models, to aid our understanding of problems.
What is a model?
A construct or representation of processes or behaviors in the real world. For complex systems, models frequently are simulations that use data or observations and mathematical equations to describe and quantify response over time.
Models that support decisions or group discussion about hard problems are one of the most powerful tools we can use to achieve better outcomes for complex issues. Models are invaluable tools to use because we know that they are useful for:
- Making our understanding of problems explicit
- Helping us define important elements and behaviors in the systems
- Enabling forward looking analyses and evaluation of potential scenarios
- Generating candidate solutions that may help us achieve more satisfying outcomes
- Supporting substantive conversations among stakeholders about important and difficult issues or concerns.
Ultimately, models help us learn about and explore realities of complex problems more effectively. In short, we know that models add value to our understanding and sense-making about the world.
Learn More at ModelMuse, a video series that delves more deeply into considerations of modeling for complexity.
Biography: Dr. Suzanne A Pierce is a Research Scientist at the Texas Advanced Computing Center (TACC) and a Lecturer with the Jackson School of Geosciences at the University of Texas at Austin (UT-Austin). Dr. Pierce has extensive experience in integrated modeling, participatory decision support, and scientific research for groundwater and energy-water-mining case studies. She leads the Dynamic Decision Support team which is housed in the Data and Statistics group at TACC. Her focus is on developing generalized decision support systems, integrated models, and cyberinfrastructure tools for Earth Resources Management. She teaches case-based computational modeling skills and leads a dual exchange field program between Mexico and the US for applications of Intelligent Systems to Geosciences.
This blog post is one of a series resulting from the first meeting in March 2016 of the Core Modelling Pursuit. This pursuit is part of the theme Building Resources for Action-Oriented Team Science through Syntheses of Practices and Theories funded by the National Socio-Environmental Synthesis Center (SESYNC).